Module ECON40B15: Financial Technologies I

Department: Economics

ECON40B15: Financial Technologies I

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• Financial Technologies (FinTech) encompass the set of software, hardware, and innovative algorithmic technologies typically employed by and across the financial innovation landscape.
• This is designed to be a primer on FinTech and serves as a platform for further skills and development in this area. 
• The aim of this course is to provide a comprehensive introduction to FinTech, including Machine Learning in Finance, Textual Analysis, Marketplace Lending, Crowdfunding, Blockchain, Distributed Ledger Technology (DLT) and Decentralized Finance, Initial Coin Offerings (ICOs), Cryptocurrency and Stablecoins, Central Bank Digital Currencies (CBDCs), Robo Advising and Automated Assert Management, Cyber Security and Regulation of FinTech.
• Students will finish the course with both a technical, social and economic understanding of Financial Technologies with a comprehensive knowledge of key concepts and innovations. 
• This course will provide a summary and guidance on the types of technologies typically deployed and is pitched at those in a management or deployment role rather than a developer or software engineer.
• Students do not require any specific programming experience, this course will be self-contained in this respect and does not assume any prior knowledge.

Content

• The area of Financial Technologies evolves year on year; hence, the following list is indicative and subject to some evolution:
• Overview of the Industry: What is Fintech and Why Now
• Machine Learning in Finance
• Textual Analysis and Unstructured Data
• Credit Scoring and Marketplace Lending
• Equity Crowdfunding
• Blockchain and Cryptocurrencies
• Initial Coin Offerings (ICOs)
• Stablecoins and Central Bank Digital Currency (CBDC)
• Robo Advising and Automated Asset Management
• Cybersecurity and Regulation of Fintech

Learning Outcomes

• By the end of the module students should be able to:
• Identify the core components of the new financial technologies.
• Be able to sketch the design framework for new types of financial instruments.
• Understand the role of Artificial Intelligence and Machine Learning in financial services.
• Understand the underlying technical solutions needed to assess the risk of new financial products.

• Introductory programming skills, scripts and infrastructure.
• System architectures
• Applied modelling techniques
• Introductory cryptographic methods for finance

• Written Communication;
• Planning, Organising and Time Management;
• Problem Solving and analysis;
• Using initiative;
• Numeracy;
• Computer Literacy

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• A combination of lectures, seminars and guided reading will contribute to achieving the aims and learning outcomes of this module. Summative assessment will test students' knowledge and understanding of the subject-matter, their critical judgement and problem-solving skills.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Group work and discussion in seminars and online discussion board for Q&A. Oral feedback in a flipped classroom environment.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University